Monitoring resource consumption of commercial buildings is becoming increasingly desirable, especially as resource prices increase and corporate sustainability reporting becomes more common. As a means to decrease cost, specific equipment with high resource demands is often targeted for upgrades or replacement. However, existing site-level metering techniques do not allow for the identification of such equipment.
Although metering solutions have been used to monitor and report flows of resources, few are available at a cost low enough for metering to penetrate the lower-level end loads of resource use. Thus, detailed analysis becomes difficult, and resource use at the end load level is often unclear. Quantifying resource use at such lower-level end loads is desirable, since opportunities for resource use reduction often exist at the lower-level end loads.
Smart meters have been deployed across a wide range of buildings and campuses to assess the consumption of resources. However, the cost of smart meters often restricts smart meter instrumentation to site-level data collection. Although such high-level metering provides sufficient data to extract summary statistics about the overall resource consumption of a site, such meters fail to provide adequate detail about the specific manner by which resources are being consumed.
Current disaggregation techniques may be used to gain insight into the types of loads underlying a front-end metering location by allowing for the analysis of consumption data based on individual areas within a site. However, current disaggregation techniques are generally limited to small-scale installations, such as homes, or utilize specialized hardware, such as high-frequency sampling, in order to gain insights. Therefore, disaggregation techniques have historically been of limited use in commercial or industrial environments.
Another technique that is currently used within the industry involves branch metering of homogeneous loads. For example, by installing a single meter on a branch for which the loads are known to be exclusively lighting, one can disaggregate the fraction of energy going towards lighting. However, such homogeneous branches are generally only found in newer buildings or buildings with a small number of loads. By contrast, for the large base of commercial and industrial sites that were built a decade or more ago, the loads on a given branch are rarely homogeneous. Thus, top-level meters typically do not provide appropriate insight into end load use.
In addition, some customers have installed large numbers of meters in order to generate real-time insights into resource use. However, such an approach typically incurs fairly large costs and, thus, is generally not viable for mass deployment across a large number of sites.